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farseg's Introduction

Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery



This is an official implementation of FarSeg in our CVPR 2020 paper Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery.


Citation

If you use FarSeg in your research, please cite the following paper:

@inproceedings{zheng2020foreground,
  title={Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery},
  author={Zheng, Zhuo and Zhong, Yanfei and Wang, Junjue and Ma, Ailong},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4096--4105},
  year={2020}
}

Getting Started

Install SimpleCV

pip install --upgrade git+https://github.com/Z-Zheng/SimpleCV.git

Requirements:

  • pytorch >= 1.1.0
  • python >=3.6

Prepare iSAID Dataset

ln -s </path/to/iSAID> ./isaid_segm

Evaluate Model

1. download pretrained weight in this link

2. move weight file to log directory

mkdir -vp ./log/isaid_segm/farseg50
mv ./farseg50.pth ./log/isaid_segm/farseg50/model-60000.pth

3. inference on iSAID val

bash ./scripts/eval_farseg50.sh

Train Model

bash ./scripts/train_farseg50.sh

farseg's People

Contributors

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Stargazers

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